Wireless Network Localization Algorithm Based on Tikhonov Regularization for Anisotropic Networks

Abstract

In anisotropic network, hop-counts between nodes may not match physical distances well. Hence, it may introduce huge errors to employ multi-hop range-free localization algorithm to estimate nodes location. In this paper, we present a novel multi-hop range-free localization algorithm for anisotropy network. Firstly, we build the relationship between hop-counts and distances among nodes under Tikhonov regularization metric. Since the relationship retains all the hop-counts characteristics to all anchors in all directions, then we can precisely capture the anisotropic relationship between hop-counts and physical distances. Finally, we use the multilateration technique to estimate the locations of all nodes. We evaluate our method based on multiple anisotropy factors, and analyze its performance. We also compare our method with state-of-art methods, and demonstrate the high efficiency of our proposed method. Experiments results show that proposed algorithm improves localization accuracy by more than 90%.